The present invention relates to a color image sensor having a plurality of a sensor element and associated filters.
When manufacturing or producing color image sensors, which are used in the field of consumer electronics, in the industrial field, in the field of medical technology and in the field of cinema and television, mainly CMOS image sensors are used, whose image points (pixels) are provided with individual or planar color filters, mainly red, green and blue. Subsequently, the color filters can no longer be altered in their characteristics.
Known color image sensors have invariable color filters and comprise a plurality of sensor elements (pixel), which are arranged on a substrate. Every sensor element (pixel) is provided with a color filter, wherein the color filters of a plurality of sensor elements can be arranged to form a Bayer filter mask. The Bayer filter mask consists of 50% green, one quarter (25%) red and one quarter (25%) blue color filters. The color filter distribution considers the higher sensitivity of the human eye with regard to green hues. Further examples of color image sensors can be found in DE 69 712 969 T2, DE 69 131 076 T2, DE 69 316 261 T2 and DE 69 626 970 T2. In the color image sensors shown there, only one color value each is available for every image point (pixel) of the color image sensor. The two missing pieces of color information have to be determined by interpolation with the help of the adjacent image points (pixel). The main problem is now to find suitable interpolation algorithms which are, on the one hand, realizable, and which can, on the other hand, accurately detect and reconstruct, for example, edges up to the resolution limit.
For evaluating data, a high number of possible methods exist. Examples can be found in DE 69 729 648 T2, DE 102 006 038 646 A1, DE 69 922 129 T2 and DE 102 006 013 810 B4. Further, the application of suitable interpolation algorithms aims to correct erroneous image points (pixels) as well as to accurately detect and reconstruct edges. This is described, for example, in DE 102 006 050 864 and DE 69 801 978 T2. Further, image reproduction devices exist having multilayered LCD filters allowing an adjustment of the transmission for all three primary colors (red, green and blue) as described U.S. Pat. No. 5,686,931.
A further currently used method is based on the usage of several (mainly three) sensor elements together with a beam splitter and different planar color filters (mainly red, green and blue) in front of one sensor element each. This embodiment provides all necessitated color information for each image point (pixel). However, this embodiment necessitates a lot of effort, is expensive and necessitates a lot of space. Further, optical problems caused by the beam splitter complicate the usage. For example, the beam splitter can cause chromatic aberration.
Caused by production tolerances and processes such as aging and thermal impact, the characteristics of the individual image points (pixels) of the color image sensor can change. Particularly in high-quality color image sensors for film and TV, it is desirable to compensate this effect. However, calibration is frequently very expensive since, at first, the color image sensor has to be exposed to images of different brightness and evenly illuminated images. From the captured images, correction values for amplification, offset and linearization can be calculated for every individual image point (pixel). To ensure optimum quality of the color image sensor at any time, camera users have to be able to perform recalibration in the field. Since, however, exact illumination of several different images and different manual interventions are necessitated for calibration, recalibration is normally avoided. The effort and the risk of useless images after erroneous recalibration are too high.
A further problem when using digital image sensors is the limited dynamic range. Currently, image sensor producers try to expand the dynamic range of the image sensors by different technologies which, however, normally involve tradeoffs. The applied methods either result in temporal or local blur.